Journal article

A new peak detection algorithm for MALDI mass spectrometry data based on a modified Asymmetric Pseudo-Voigt model

C Wijetunge, I Saeed, BA BOUGHTON, U Roessner, SK Halgamuge

BMC Genomics | BioMed Central | Published : 2015

Abstract

Background Mass Spectrometry (MS) is a ubiquitous analytical tool in biological research and is used to measure the mass-to-charge ratio of bio-molecules. Peak detection is the essential first step in MS data analysis. Precise estimation of peak parameters such as peak summit location and peak area are critical to identify underlying bio-molecules and to estimate their abundances accurately. We propose a new method to detect and quantify peaks in mass spectra. It uses dual-tree complex wavelet transformation along with Stein's unbiased risk estimator for spectra smoothing. Then, a new method, based on the modified Asymmetric Pseudo-Voigt (mAPV) model and hierarchical particle swarm optimizat..

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Grants

Awarded by Australian Research Council


Funding Acknowledgements

We gratefully acknowledge an anonymous reviewer for providing constructive comments to improve the manuscript. This work is partially funded by Australian Research Council grant DP150103512. CDW is fully funded by IPRS and APA scholarships of The University of Melbourne.